Nvidia 50 Series (Blackwell) support thread: How to get ComfyUI running on your new 50 series GPU.

[comfyanonymous]

I will try keeping this post up to date as much as possible with the latest developments.

To get your nvidia 50 series GPU working with ComfyUI you need a pytorch that has been built against cuda 12.8

In the next few months there will likely be a lot of performance improvements landing in pytorch for these GPUs so I recommend coming back to this page and updating frequently.

Windows

Windows users can download this standalone ComfyUI package with a cuda 12.8 torch build

Manual Install

At this moment Blackwell is not yet supported by stable pytorch.

pytorch nightly cu128 is available for Linux:

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128

You can also use the Nvidia Pytorch Docker Container as an alternative which might give more performance.

Link: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

Here's how to use it:

docker run -p 8188:8188 --gpus all -it --rm nvcr.io/nvidia/pytorch:25.01-py3

Inside the docker container:

git clone https://github.com/comfyanonymous/ComfyUI
cd ComfyUI
grep -v 'torchaudio\|torchvision' requirements.txt > temp_requirements.txt
pip install -r temp_requirements.txt
python main.py --listen

[mcmonkey4eva]

There are also Windows prebuilt wheels of pytorch on cuda 128 that nvidia gave w-e-w to publish https://huggingface.co/w-e-w/torch-2.6.0-cu128.nv

[mmartial]

FYSA, the nightly for 12.8 appears available https://download.pytorch.org/whl/nightly/cu128

[comfyanonymous]

Yeah I see the package but it's still missing the cu128 torchvision, torchaudio and windows packages.

[mmartial]

It is. Thanks for clarifying the components we are waiting for.

I was trying to follow the guide by removing torchvision and torchaudio
and doing a pip3 install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu128

spandrel too uses torchvision, which forces a downgrade on a Linux installation within a virtualenv.
https://github.com/chaiNNer-org/spandrel/blob/main/libs/spandrel/pyproject.toml#L36

EDIT: I will postpone testing until this is ready. Thanks for the details

[comfyanonymous]

I just noticed there are now nightly torchvision and torchaudio cu128 wheels for Linux. No windows packages yet though.

I tried them and they seem to work well so I have updated the post.

[mmartial]

Thank you 👍

With this news, I have made an updated release of https://github.com/mmartial/ComfyUI-Nvidia-Docker

For CUDA 12.8, I pre-install torch using pip3 install --pre torch torchaudio torchvision --index-url https://download.pytorch.org/whl/nightly/cu128 before installing ComfyUI from git and installing its requirements. I have tested it and can generate the bottle :)

No 50xx yet for me, so this test was done on a 3090 with driver 570 installed.

[edisonchan]

The Windows version said:
ModuleNotFoundError: No module named 'torchaudio'

[comfyanonymous]

This is because there was no torchaudio cu128 package provided.

The only thing this affects is the audio related nodes so it only affects you if you are using stable audio.

[edisonchan]

nf4 node does not work.

[ltdrdata]

Anything related to NF4 support should be resolved in the node pack repo that provides NF4 feature.

[edisonchan]

ImportError: tokenizers>=0.21,<0.22 is required for a normal functioning of this module, but found tokenizers==0.20.3.
Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main

How can I do to fix problem?

[adamreading]

Sorry - I have been banging my head against this for 6 hours - trying to run a cosmos workflow with 5090 - without SageAttention or TorchCompile - a 14 minute job on 4090 is taking 25 minutes. To turn them on I installed Triton and Sageattention - then I get this error afterwards whether I bypass the patch and compile or not:- KSampler
Command '['C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\bin\Hostx64\x64\cl.EXE', 'C:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k\cuda_utils.c', '/nologo', '/O2', '/LD', '/wd4819', '/IC:\Users\JoannaThompson\ComfyUI\ComfyUI_cu128_50XX\python_embeded\Lib\site-packages\triton\backends\nvidia\include', '/IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\include', '/IC:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k', '/IC:\Users\JoannaThompson\ComfyUI\ComfyUI_cu128_50XX\python_embeded\Include', '/IC:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\include', '/IC:\Program Files (x86)\Windows Kits\10\Include\10.0.26100.0\shared', '/IC:\Program Files (x86)\Windows Kits\10\Include\10.0.26100.0\ucrt', '/IC:\Program Files (x86)\Windows Kits\10\Include\10.0.26100.0\um', '/FoC:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k\cuda_utils.cp312-win_amd64.obj', '/link', '/LIBPATH:C:\Users\JoannaThompson\ComfyUI\ComfyUI_cu128_50XX\python_embeded\Lib\site-packages\triton\backends\nvidia\lib', '/LIBPATH:C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\lib\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', '/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.42.34433\lib\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\ucrt\x64', '/LIBPATH:C:\Program Files (x86)\Windows Kits\10\Lib\10.0.26100.0\um\x64', 'cuda.lib', '/OUT:C:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k\cuda_utils.cp312-win_amd64.pyd', '/IMPLIB:C:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k\cuda_utils.cp312-win_amd64.lib', '/PDB:C:\Users\JOANNA1\AppData\Local\Temp\tmpy8t3476k\cuda_utils.cp312-win_amd64.pdb']' returned non-zero exit status 2.

I have run this through GPT and followed every instruction. Step 1: Verify CUDA Toolkit Installation
Run the following command in ComfyUI's embedded Python:

python
Copy
Edit
import torch
print(torch.version.cuda)
Expected Output: 12.8

If it does not match 12.8, you may need to reinstall PyTorch with the correct CUDA version.

✅ Step 2: Check NVIDIA Toolkit and Drivers
Ensure you have the latest NVIDIA GPU driver and CUDA toolkit installed.

Update your NVIDIA driver (Download latest)
Confirm CUDA installation with:
powershell
Copy
Edit
nvcc --version
Expected Output: release 12.8
If not, reinstall CUDA 12.8 from NVIDIA.

✅ Step 3: Fix Microsoft Visual Studio Build Tools
Open Developer Command Prompt for VS 2022

Run:

sh
Copy
Edit
cl.exe
If it says command not found, reinstall Microsoft C++ Build Tools:
Download: Visual Studio Build Tools 2022
Install:
C++ CMake tools for Windows
MSVC v143 - VS 2022 C++ x64/x86 build tools
Windows 10 SDK (latest version)
Restart the PC.

[rubentorresbonet]

anyone knows if other pytorch's cuda versions like 12.6 will work with blackwell?

[mpfcs162]

No, Blackwell GPUs require 12.7 or newer IIRC.
Edit: So 12.8 since that is the current version. It's a new architecture so I guess it makes sense that 12.6 and older versions are not supported. CUDA is not backwards compatible?

[fasfafefggwgrw]

When I use [ComfyUI package with a cuda 12.8 torch build], many custom_nodes are "IMPORT FAILED" including Manager, InstantID, ReActor ...

[Shad0w23333]

same, is is possible to build a PyTorch that works for 50s?

[mpfcs162]

Check Python version, reinstall dependencies, and look for incompatibilities in the logs - some nodes might need updates for CUDA 12.8. Fresh install or upgrade?

[Shad0w23333]

I will try keeping this post up to date as much as possible with the latest developments.

To get your nvidia 50 series GPU working with ComfyUI you need a pytorch that has been built against cuda 12.8

In the next few months there will likely be a lot of performance improvements landing in pytorch for these GPUs so I recommend coming back to this page and updating frequently.

Windows

Windows users can download this standalone ComfyUI package with a cuda 12.8 torch build

Manual Install

At this moment Blackwell is not yet supported by stable pytorch.

pytorch nightly cu128 is available for Linux:

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128

You can also use the Nvidia Pytorch Docker Container as an alternative which might give more performance.

Is is possible to build a pytorch that works for 5090? If so how to do it?

[mpfcs162]

What do you mean? There is already one for CUDA 12.8: https://download.pytorch.org/whl/nightly/cu128/torch/ For Windows you can try the EA version found here: https://huggingface.co/w-e-w/torch-2.6.0-cu128.nv Or just use the standalone package linked above with a CUDA 12.8 torch build.

We spent 6 hours + yesterday trying to install comfyui portable around the special version at the top of the screen. It wont let me run Sageattention or Torchcompile in workflows - and because it’s missing TorchAudio - things I use every day like GripTape won’t load into custom nodes any more. Running the cosmos workflow without sage and compile - is twice as long as on a 4090 system (25 mins for 8 sec gen compared to 14 minutes on 4090) Although I was able to install SageAttention and Triton I don’t think they are working with this version of PyTorch

Have you checked the logs for errors or tried a clean environment to rule out conflicts?

[adamreading]

What do you mean? There is already one for CUDA 12.8: https://download.pytorch.org/whl/nightly/cu128/torch/ For Windows you can try the EA version found here: https://huggingface.co/w-e-w/torch-2.6.0-cu128.nv Or just use the standalone package linked above with a CUDA 12.8 torch build.

We spent 6 hours + yesterday trying to install comfyui portable around the special version at the top of the screen. It wont let me run Sageattention or Torchcompile in workflows - and because it’s missing TorchAudio - things I use every day like GripTape won’t load into custom nodes any more. Running the cosmos workflow without sage and compile - is twice as long as on a 4090 system (25 mins for 8 sec gen compared to 14 minutes on 4090) Although I was able to install SageAttention and Triton I don’t think they are working with this version of PyTorch

Have you checked the logs for errors or tried a clean environment to rule out conflicts?

Yes we went through the logs - they are in the earlier post above - we tried for 6 hours downloading different versions - Visual build tools, various Nvida toolkits - did everything GPT suggested - its a brand new out of the box machine - nothing previously installed except office.

[adamreading]

5090 Crash 10.txt
One of the complete logs

[mpfcs162]

Tried running Linux? https://download.pytorch.org/whl/nightly/cu128/torch/
To my knowledge there is no official Windows build of PyTorch that supports 12.8 yet.
Sorry I can't offer more help...

[adamreading]

Tried running Linux? https://download.pytorch.org/whl/nightly/cu128/torch/ To my knowledge there is no official Windows build of PyTorch that supports 12.8 yet. Sorry I can't offer more help...

Thanks for looking. The app I want to run (a comfyui-discord bot) requires portable and lm
Studio to work apparently. Plus I use the machine for office365 at the same time lol. Looks like I just have to be patient and work out what will run and what won’t. It ran an ltxv video generator in 36 seconds so some stuff is ok. Couldn’t load anything Pulid.

[adamreading]

Having given up on Portable for now - too many errors lol - I am using WSL - Ubuntu - everything else is set up and working in Comfyui - I have the latest pytorch nightly from pip install --pre torch torchvision torchaudio --index-url[ https://download.pytorch.org/whl/nightly/cu128] - but when I use Sageattention I get this:
loaded completely 29493.675 3667.902587890625 True
0%| | 0/80 [00:00<?, ?it/s]'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
'sm_120' is not a recognized processor for this target (ignoring processor)
LLVM ERROR: Cannot select: intrinsic %llvm.nvvm.shfl.sync.bfly.i32
Aborted (core dumped)

[adamreading]

I managed to get it working in Windows yesterday. Had to manually install the torch-2.6.0+cu128.nv-cp312-cp312-win_amd64.whl and torchvision-0.20.0a0+cu128.nv-cp312-cp312-win_amd64.whl.

Originally had the wrong Python version installed. Easy fix but took me a long time (longer than I want to admit) to figure out...

There are some errors though (torchaudio missing), but I'm running SD 3.5 L to test on a 5090 and I get output. And fast too. But 32GB VRAM is not as much as I'd hoped and the impact compared to a 4090 is not that big - about ~30% faster which is expected I guess...

But I'd honestly recommend just running it on Linux atm.
Yeah - I spent the last 6 hours trying to set all the stuff up - had to compile sageattention and apex - xformers I don't think is compatible yet - running it after lunch to test

[Shad0w23333]

I managed to get it working in Windows yesterday. Had to manually install the torch-2.6.0+cu128.nv-cp312-cp312-win_amd64.whl and torchvision-0.20.0a0+cu128.nv-cp312-cp312-win_amd64.whl.

Originally had the wrong Python version installed. Easy fix but took me a long time (longer than I want to admit) to figure out...

There are some errors though (torchaudio missing), but I'm running SD 3.5 L to test on a 5090 and I get output. And fast too. But 32GB VRAM is not as much as I'd hoped and the impact compared to a 4090 is not that big - about ~30% faster which is expected I guess...

But I'd honestly recommend just running it on Linux atm.

Wait, can u explain how to do that? Thank u

[mpfcs162]

Wait, can u explain how to do that? Thank u

Do what?

[adamreading]

I managed to get it working in Windows yesterday. Had to manually install the torch-2.6.0+cu128.nv-cp312-cp312-win_amd64.whl and torchvision-0.20.0a0+cu128.nv-cp312-cp312-win_amd64.whl.

Originally had the wrong Python version installed. Easy fix but took me a long time (longer than I want to admit) to figure out...

There are some errors though (torchaudio missing), but I'm running SD 3.5 L to test on a 5090 and I get output. And fast too. But 32GB VRAM is not as much as I'd hoped and the impact compared to a 4090 is not that big - about ~30% faster which is expected I guess...

But I'd honestly recommend just running it on Linux atm.

Have you managed to get SageAttention working yet? (With Linux or Windows)

[mpfcs162]

No. I assume it won't be fully stable until we see an official release of PyTorch with CUDA 12.8 support. Or req some additional manual config. I just can't be bothered with that at this point. Been stuck in integration hell all day trying to troubleshoot some code for a client so haven't had much time to dig further into this topic. Sorry.

[Teuflor]

im using comfyui over pinokio, is there any way to update my comfy to work with my new 5080?

i deleted the old files and changed in the torch.js on the patch above, but it wont start

[gachapengames]

Will using a docker allow for a working torchvision in windows?

[Six6pounder]

@gachapengames Yes, use nvcr.io/nvidia/pytorch:25.01-py3 as image and it works

[gachapengames]

Can someone write a little guide for getting a docker running torchvision, etc on window with the portable Blackwell comfyui release? Please write it for a normal user who has no programming knowledge.

There are basic instructions in the OP, but what even is a docker?

"docker run -p 8188:8188 --gpus all -it --rm nvcr.io/nvidia/pytorch:25.01-py3"

Where is this command supposed to be run? Is a docker something to be installed to system python or standalone folder?

How would this be installed on a fresh portable comfyui install?

With more Blackwell cards trickling out, there will most likely be more users needing help setting this up. Thank you.

[mmartial]

Please check the "Windows: WSL2 using podman" from https://github.com/mmartial/ComfyUI-Nvidia-Docker

With the caveat that you will need to adapt the podman run line if you want to use the proposed containers to be something like (adapted to attempt to reflect the above order):

podman run --userns=keep-id -p 8188:8188 --device nvidia.com/gpu=all --rm -it nvcr.io/nvidia/pytorch:25.01-py3

with the caveat that everything will be stored within the container since you have no mount (the -v from my original writeup)

so maybe:

podman run --userns=keep-id -p 8188:8188 --device nvidia.com/gpu=all --rm -it -v `pwd`/comfy:/comfy nvcr.io/nvidia/pytorch:25.01-py3

and then do the other steps listed above (pip install...) after cd /comfy so that the files persist when you exit the container

[gachapengames]

To anyone having trouble with the portable version for Blackwell gpus, do not update it! I noticed during updating that it uninstalled the cu128 and installed another version for example. Torchvision works with a fresh install without updating!

[mpfcs162]

Just want to add that this is also a common issue for packages and custom setups right now. They might come with their "own" PyTorch included and since there isn't an official release yet they will be unable to update to a version that supports CUDA 12.8. Or they run an automatic update during the install process that overrides the PyTorch version you already had installed. You can still update though - just need to reinstall the correct version of PyTorch.

Another common issue that people might have is that they match it with the wrong version of Python. Make sure you have the correct version installed before you proceed (e.g. "cp310" meaning Python 3.10.XX). This might be obvious to most but for new users I can imagine this is a step that can cause a lot of headache.

[adamreading]

Just want to add that this is also a common issue for packages and custom setups right now. They might come with their "own" PyTorch included and since there isn't an official release yet they will be unable to update to a version that supports CUDA 12.8. Or they run an automatic update during the install process that overrides the PyTorch version you already had installed. You can still update though - just need to reinstall the correct version of PyTorch.

Another common issue that people might have is that they match it with the wrong version of Python. Make sure you have the correct version installed before you proceed (e.g. "cp310" meaning Python 3.10.XX). This might be obvious to most but for new users I can imagine this is a step that can cause a lot of headache.

So far I’ve had to reinstall from scratch about once a day. It’s super tedious. Install a workflow. Add all the nodes, no longer starts. 100s of errors. This is using the Windiws Stand Alone at the top of the thread. Could you give me the exact pip install command to reinstall torch and torch vision from the Nvidia links shared above, that would help when I get stuck. I tried every combination I could think of or GPT and none worked lol. Up til now i just back up the model directory and start again.

[mpfcs162]

So I've used both Comfy UI and Stability Matrix with SD Forge WebUI these past days since getting my 5090.

Each instance needs to have the correct version of Torch, and updating/installing will not ensure that (edit: if anyone reads this in the future there will eventually be an official torch release that supports CUDA 12.8 and in that case what is written here might no longer valid). Best way is to install Torch from the files above, making sure you use the correct version for your system and Python install. For SM, you need to install it to the package directly for example.

And please, do not run commands you find online unless you understand what they do. This applies to the below commands as well.

Navigate to the correct dir and type this to uninstall torch, torchvision and torchaudio:
python_embeded\python.exe -m pip uninstall -y torch torchvision torchaudio

Then, for ComfyUI at least, you can run this. Adjust the command as needed:
python_embeded\python.exe -m pip install H:\torch\torch-2.6.0+cu128.nv-cp310-cp310-win_amd64.whl H:\torch\torchvision-0.20.0a0+cu128.nv-cp310-cp310-win_amd64.whl

You can run this in your dir to check what is installed:
python_embeded\python.exe -m pip list

[mpfcs162]

I just want to add that asking chatGPT (and similar LLMs) about this might not be as helpful as you think.

A very common issue is coherence with these models, and they can easily spew out answers that look and seem correct, while in reality are not what you actually need. For example, if I ask it why I'm getting kernel error when attempting to run stock ComfyUI it will tell me to update using a pip command, but it will give me a link to a build that does not exists (cu127) since it believes that CUDA 12.7 is the version I need for my 5090 since that is the min. version of CUDA that Blackwell supports.

I can follow that trail together with chatGPT for hours and end up trying to compile my own version, uninstall/reinstall various extensions and packages and get absolutely nowhere. And chatGPT will always act and respond with 100% confidence no matter what, and I will never figure out the culprit unless I go to the repo or follow the trail myself to discover that it (cu127) does not exists.

Of course, LLMs are great for a number of reasons - but beware when trying to do stuff like this that the output might be complete nonsense.

[adamreading]

I just want to add that asking chatGPT (and similar LLMs) about this might not be as helpful as you think.

A very common issue is coherence with these models, and they can easily spew out answers that look and seem correct, while in reality are not what you actually need. For example, if I ask it why I'm getting kernel error when attempting to run stock ComfyUI it will tell me to update using a pip command, but it will give me a link to a build that does not exists (cu127) since it believes that CUDA 12.7 is the version I need for my 5090 since that is the min. version of CUDA that Blackwell supports.

I can follow that trail together with chatGPT for hours and end up trying to compile my own version, uninstall/reinstall various extensions and packages and get absolutely nowhere. And chatGPT will always act and respond with 100% confidence no matter what, and I will never figure out the culprit unless I go to the repo or follow the trail myself to discover that it (cu127) does not exists.

Of course, LLMs are great for a number of reasons - but beware when trying to do stuff like this that the output might be complete nonsense.

I concur from personal experience - however as someone who doesn't understand this stuff - and having had an incredible machine arrive a week ago, that I just couldn't get to work - and all my techie friends on discord were at a loss as well - ChatGPT was my only option. Since talking to LLMS is what i do a lot for work etc, I just kept everything inside one thread - so it remembered everything we had been doing - I used its commands to trouble shoot - but used my brain to realise when we were repeating or when it had forgotten about having to use 12.8 sm_120 etc and kept reminding it of these things - and with a little prompting it helped me through a maze of tests and trials I never would have got through on my own. In the end - I went back to the original Comfy Windows stand alone install thats at the top of the page. I learned to install custom nodes in new workflows - 1 at a time, restarting and checking the logs after every node - and trouble shooting anything that threw up one step at a time. And it's now pretty much running. It is slow however - without SageAttention or FlashAttention etc I think it struggles. And I am sure there will be more performance increases as more tools get compiled to use its abilities. I am old and have been around a while - so I realise that life at the bleeding edge is not always easy. I am still confused about what the difference is between Comfyui Stand Alone and Comfyui Portable - half my friends are saying go one way the other the other - but I think they are just two different names for the same install? As far as I can tell (having installed all of these this week - for a Windows machine the options are 1) Desktop Comfy that installs from an exe file - doesn't open in a browser - has a built in terminal in the bottom pull up in a tab next to the logs, but seemed restrictive to use (though I can't tell you why). 2) The Windows Stand Alone I am currently using - which, once you figure out where to run the pip commands etc is pretty straight forward, easy to back up directories - or reinstall by dragging the zip file over the top again 3) WSL - allowed me to use TorchAudio right away - feels like gets quicker support from the community because its in Linux - but got quite complicated very quickly - and installing an unrelated program in a docker in the same WSL killed the whole thing - and I lost everything and no way to recover my files... @mpfcs162 a case in point for your statement - ChatGPT told me to remove the WSL to clear the issue with YuE and gave me the command to run - which I did - and then it wiped everything. (My own fault)

[Tathiane123]

Excelente

[Tayyab-H]

Are there no windows pytorch options available for cuda 12.8 still? Any help would be greatly appreciated.

[adamreading]

I couldn't find the 3b but I am downloading this to test memory lmstudio-community/Qwen2.5-7B-Instruct-1M-GGUF/Qwen2.5-7B-Instruct-1M-Q4_K_M.gguf

[adamreading]

Looks like you can import any model though - https://lmstudio.ai/docs/basics/import-model

[adamreading]

looks like 2gb of my gpu VRAM is there used all the time with nothing obviously running - then adding a 5gb Quen took it up to 7GB

[adamreading]

llava 1.5 used 12gb VRAM ran super fast

[Tayyab-H]

thanks for the help! Ill give LM studio a try! Its a shame it isnt working through code, id love to build stuff with it.

[alisson-anjos]

For those who want to use Sage Attention + Hunyuan + RTX 50xx with a simple tutorial, it is interesting to keep the files inside WSL instead of using the files in Windows due to the reading time (you can test it and you will understand) that's why I recommend copying your comfyui to WSL.

https://github.com/alisson-anjos/ComfyUI_Tutoriais/blob/main/WSL/install.md

Notes:

It is necessary to use the kijai patch node for sage attention because it currently only works with native sage attention and not varlen, at the end of the README there is a workflow with this node.

And for those who want to compile SageAttention due to some lack of compatibility with the OS, it is necessary to compile Triton and then Sage Attention, to compile Sage Attention it is necessary to change setup.py with the code in this issue: [Sage Attention Issue] (thu-ml/SageAttention#107 (comment))

Thanks to Kijai for precompiling triton and sage attention.

[adamreading]

Thanks so much for making this, you really saved me from brain destruction this afternoon, and I’m glad it will help others as well. I can’t tell you how appreciated this was!! (AJO FittyNunty)